The invention relates to a voice-optimized database and a method of using audio vector valuation to search a voice-optimized database and to enhance existing, non-voice-enabled databases to perform searches from spoken queries.
Existing electronic shopping cart technology is limited to serving customers who access online shopping sites using HyperText Markup Language (HTML) or other markup language browsers. Currently, no audio-capable electronic shopping cart exists for use with any kind of audio interface such as a telephone, or a computer with a microphone and voice output capability (e.g., voice over the Internet). Furthermore, no telephony interface exists which allows telephone customers to purchase goods offered via online shops.
To illustrate the above-described limitations, a conventional system 10 is depicted in FIG. 1 for shopping via the Internet 18. A user computer 12 (e.g., a personal computer or PC) having browser software 14 can connect via the public switched telephone network (PSTN) or other network 16 to an online shop 20 using different methods such as typing the Uniform Resource Locator (URL) of the online shop, if known, or selecting an online shop or the type of item desired from a home page generated at the PC. While browsing the online shop 20, the user PC 12 receives a number of HTML or Web-type pages for guiding the user when searching for one or more items to purchase and for completing the transaction by a payment method such as a credit card transaction. The transaction can be monitored using a shopping cart 22. An exemplary Web page 24 for allowing a user to conduct a search of items available via an online shop is depicted in FIG. 2. The description of the existing electronic shopping system 10 in FIG. 1 and of the illustrated embodiments of the present invention provided herein will be with reference to an online shop for purchasing books. It is to be understood that various aspects of the present invention can be used with any online shop or catalogue, as well as with any database for applications other than online shopping.
FIG. 3 depicts a conventional database 30 which comprises a number of records 32 such as a record 34 for each book in an online bookshop catalogue. Each record 34 has a number of fields 36, 38, 40, 42 and 44 for entering such information as the book title, author, subject matter, price, ISBN, respectively, among other information. As indicated by the onscreen buttons 40, 48, 50 and 52 in FIG. 2, the Web page 24 provides a user with the option of searching for a book on the basis of book title, author or subject, as well as searching the entire record for each book. The online shop can provide the online user with more specific search pages when one of the three buttons is selected. A processor 31 at the online shop generally searches one or more database fields using the text of the electronic query (e.g., xe2x80x9cGone With the Windxe2x80x9d) 54 entered by a user via a Web page. The results of the search following the electronic query are then presented to the user PC via another Web page. If the search results locate an item desired by the user, the user can select that item for placement in an electronic shopping cart. Conventional electronic shopping carts 22 maintain a record of items selected by a user during a browsing session and can assist the user in completing a payment transaction to purchase some or all of the items in the electronic shopping cart during the browsing section or at the conclusion of the browsing session.
Since the online shop 20 receives text queries and reports search results via HTML pages, a user must have a computing device with a browser in order to search for an item available via the online shop, as well as to complete an electronic payment transaction as is the case with many online services. In addition, conventional electronic shopping carts are characterized by a number of drawbacks. Many existing electronic shopping carts maintain user identification and selection data for only a predetermined period. The shopping cart information for a user is generally removed from the server of the online shop shortly after a transaction is completed. The shopping cart information for a browsing session can also be removed during a browsing session after a prolonged period of inactivity. Thus, a user may have to repeat the browsing and shopping cart functions if the transaction data is removed from the server prior to the user making a final selection and purchase of database items.
Also, no database access system exists which allows data input based on spoken words, or has built-in search mechanisms for spoken queries. A built-in mechanism for spoken queries is different from providing a speech recognition system as an input mechanism to a database. In such a system, the speech recognition system receives audio samples, and converts the audio samples to text as though they were typed (e.g., entered in an onscreen query window such as in FIG. 2). The speech recognition system then sends the text output to the database for searching record field(s) based on text. The database has no means of searching based on a audio sample itself. Thus, a voice-optimized database is needed which permits an intelligent search of database records in response to spoken words.
The present invention overcomes the deficiencies of existing databases and realizes a number of advantages over these existing electronic systems for shopping via the internet by permitting use of spoken queries.
In accordance with an aspect of the present invention, a voice-optimized database system uses an Audio Vector Valuation (AVV) method to assign a value to every spoken query which was obtained from a speech recognition system, and then compares that to a limited set of possible outcomes, thereby making it possible to perform an intelligent search based on spoken words.
In accordance with another aspect of the present invention, each searchable item in the voice-optimized database has an associated audio vector. The audio vector comprises vector components having values for respective phonemes in the spoken name or phrase constituting the searchable item.
In accordance with still another aspect of the present invention, audio vectors determined for spoken queries are compared with audio vectors for database items to produce search results in response to spoken queries.
In accordance with still yet another aspect of the present invention, phonemes having similar pronunciation are assigned vector values which are close numerically. A distance calculation is performed between audio vectors corresponding to a spoken query and database items to produce search results.
The AVV method is used with a voice-optimized database configured in accordance with another aspect of the present invention. The AVV method can also be used as a separate mechanism to enhance existing databases which have no spoken query search capability. An AVV module is provided between a traditional speech recognition module and an existing, non-voice-enabled database. The existing database is provided with a library of phonemes and their respective values. The AVV module performs multiple queries for each spoken query. In each spoken query, the AVV module retrieves words from the database which have a similar pronunciation with the phrases received at the speech recognition module from a user.